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Low Probability of Intercept-Based Optimal Power Allocation Scheme for an Integrated Multistatic Radar and Communication System

Shi, Chenguang; Wang, Fei; Sellathurai, Mathini; Zhou, Jianjiang; Salous, Sana

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Authors

Chenguang Shi

Fei Wang

Mathini Sellathurai

Jianjiang Zhou



Abstract

This paper investigates the problem of low probability of intercept-based optimal power allocation (LPI-OPA) for an integrated multistatic radar and communication system, which consists of multiple transmitters operating at different frequencies, a radar receiver, and a communication receiver (CR). The integrated multistatic radar and communication system is capable of fulfilling the requirements of both radar and communication subsystems. The key tenet of the integrated system is to minimize the total power consumption by optimizing the transmit power allocation at each transmitter for radar waveforms and information signals, which is constrained by a predetermined target detection performance for the RR and a desired information rate for the CR. Since the analytical closed-form expression of the probability of detection is not tractable, its upper bound is derived. We analytically show that the resulting optimization problem can be reformulated as two subproblems, which can be solved by an efficient solution procedure based on the approach of linear programming and the Karush–Kuhn–Tuckers optimality conditions. Simulation results are provided to show that the LPI performance of the integrated multistatic radar and communication system can significantly be enhanced by employing our proposed LPI-OPA scheme.

Citation

Shi, C., Wang, F., Sellathurai, M., Zhou, J., & Salous, S. (2020). Low Probability of Intercept-Based Optimal Power Allocation Scheme for an Integrated Multistatic Radar and Communication System. IEEE Systems Journal, 14(1), 983-994. https://doi.org/10.1109/jsyst.2019.2931754

Journal Article Type Article
Acceptance Date Jul 25, 2019
Online Publication Date Aug 9, 2019
Publication Date Mar 31, 2020
Deposit Date Mar 25, 2020
Publicly Available Date Mar 25, 2020
Journal IEEE Systems Journal
Print ISSN 1932-8184
Electronic ISSN 1937-9234
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 14
Issue 1
Pages 983-994
DOI https://doi.org/10.1109/jsyst.2019.2931754
Public URL https://durham-repository.worktribe.com/output/1274604

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